Area-level Covariates Research Articles

Small data estimation for binary variables with big data: A comparison of calibrated nearest neighbour and hierarchical Bayes methods of estimation

A recent application in machine learning has introduced a novel approach, complemented by big data sources, aimed at providing precise estimates for small geographical areas. This method employs a dual strategy: (a) hybrid estimation, involving the integration of big data sources with imputed values derived from K nearest neighbours (KNN) to address missing target variable values from the big data source; and (b) calibration of the collective sum of small area estimates to an independent yet efficient national total. Evaluating its efficacy using simulated data from the 2016 Australian population census, the calibrated KNN (CKNN) method demonstrated superior performance compared to the Fay-Herriot method based on area-level covariates. This paper enhances the comparative analysis by contrasting the CKNN method with a hierarchical Bayes method using the logit-normal model (LN) relevant for binary data. Broadly speaking, the LN method can be viewed as the Bayesian equivalent of Battese-Harter-Fuller (BHF) method, which incorporates unit-level covariates. Our results demonstrate the CKNN method’s superiority over the LN method. However, the application of hybrid estimation to the LN method significantly diminishes this superiority. Although CKNN estimates maintain better precision, they are not as accurate as the estimates from the hybridized LN method.

Air pollution exposure and mortality from neurodegenerative diseases in the Netherlands: A population-based cohort study

BackgroundLong-term exposure to ambient air pollution has been linked with all-cause mortality and cardiovascular and respiratory diseases. Suggestive associations between ambient air pollutants and neurodegeneration have also been reported, but due to the small effect and relatively rare outcomes evidence is yet inconclusive. Our aim was to investigate the associations between long-term air pollution exposure and mortality from neurodegenerative diseases. MethodsA Dutch national cohort of 10.8 million adults aged ≥30 years was followed from 2013 until 2019. Annual average concentrations of air pollutants (ultra-fine particles (UFP), nitrogen dioxide (NO2), fine particles (PM2.5 and PM10) and elemental carbon (EC)) were estimated at the home address at baseline, using land-use regression models. The outcome variables were mortality due to amyotrophic lateral sclerosis (ALS), Parkinson's disease, non-vascular dementia, Alzheimer's disease, and multiple sclerosis (MS). Hazard ratios (HR) were estimated using Cox models, adjusting for individual and area-level socio-economic status covariates. ResultsWe had a follow-up of 71 million person-years. The adjusted HRs for non-vascular dementia were significantly increased for NO2 (1.03; 95% confidence interval (CI) 1.02–1.05) and PM2.5 (1.02; 95%CI 1.01–1.03) per interquartile range (IQR; 6.52 and 1.47 μg/m3, respectively). The association with PM2.5 was also positive for ALS (1.02; 95%CI 0.97–1.07). These associations remained positive in sensitivity analyses and two-pollutant models. UFP was not associated with any outcome. No association with air pollution was found for Parkinson's disease and MS. Inverse associations were found for Alzheimer's disease. ConclusionOur findings, using a cohort of more than 10 million people, provide further support for associations between long-term exposure to air pollutants (PM2.5 and particularly NO2) and mortality of non-vascular dementia. No associations were found for Parkinson and MS and an inverse association was observed for Alzheimer's disease.

The association between alcohol retail access and health care visits attributable to alcohol for individuals with and without a history of alcohol-related health-care use.

Alcohol retail access is associated with alcohol use and related harms. This study measured whether this association differs for people with and without heavy and disordered patterns of alcohol use. The study used a repeated cross-sectional analysis of health administrative databases. All residents of Ontario, Canada aged 10-105 years with universal health coverage (n = 10 677 604 in 2013) were included in the analysis. Quarterly rates of emergency department (ED) and outpatient visits attributable to alcohol in 464 geographic regions between 2013 and 2019 were measured. Quarterly off-premises alcohol retail access scores were calculated (average drive to the closest seven stores) for each geographic region. Mixed-effect linear regression models adjusted for area-level socio-demographic covariates were used to examine associations between deciles of alcohol retail access and health-care visits attributable to alcohol. Stratified analyses were run for individuals with and without prior alcohol-attributable health-care use in the past 2years. We included 437 707 ED visits and 505 271 outpatient visits attributable to alcohol. After adjustment, rates of ED visits were 39% higher [rate ratio (RR) = 1.39, 95% confidence interval (CI) = 1.20-1.61] and rates of outpatient visits were 49% higher (RR = 1.49, 95% CI = 1.26-1.75) in the highest versus lowest decile of alcohol access. There was a positive association between alcohol access and outpatient visits attributable to alcohol for individuals without prior health-care attributable to alcohol (RR = 1.65, 95% CI = 1.39-1.95 for the highest to lowest decile of alcohol access) but not for individuals with prior health-care attributable to alcohol (RR = 1.08, 95% CI = 0.90-1.30). There was a positive association between alcohol access and ED visits attributable to alcohol for individuals with and without prior health-care for alcohol for ED visits. In Ontario, Canada, greater alcohol retail access appears to be associated with higher rates of emergency department (ED)and outpatient health-care visits attributable to alcohol. Individuals without prior health-care for alcohol may be more susceptible to greater alcohol retail access for outpatient but not ED visits attributable to alcohol.

Long-term exposure to transportation noise and diabetes mellitus mortality: a national cohort study and updated meta-analysis

BackgroundLong-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort.MethodsDuring 15 years of follow-up (2001–2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined).ResultsHRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively).ConclusionsThis study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

Association between high levels of nitrogen dioxide and increased cumulative incidence of lung cancer in patients with idiopathic pulmonary fibrosis.

Lung cancer is a fatal complication of idiopathic pulmonary fibrosis (IPF) with a poor prognosis. However, the association between individual exposure to air pollutants and lung cancer development in patients with IPF is unknown. This study aimed to assess the effect of individual exposure to nitrogen dioxide (NO2) on lung cancer development in patients with IPF. We enrolled 1085 patients from an IPF cohort in the Republic of Korea (mean age 65.6 years, males 80.6%). We estimated individual-level long-term exposures to NO2 at the patients' residential addresses using a national-scale exposure prediction model based on data from air quality regulatory monitoring stations. To evaluate the association between NO2 levels and lung cancer development in IPF, we used an individual- and area-level covariates adjusted model as our primary model. The estimated average annual NO2 concentration was 23.1 ppb. During a median follow-up of 4.3 years, 86 patients (7.9%) developed lung cancer. NO2 concentration was associated with lung cancer development in an unadjusted model (HR 1.219; p=0.042), while a marginal association was found in the primary model (HR 1.280; p=0.084). When NO2 concentration was stratified by the median value (21.0 ppb), exposure to high NO2 levels (≥21.0 ppb) was associated with a 2.0-fold increase in the risk of lung cancer development (HR 2.023; p=0.047) in the primary model. Individual exposure to high NO2 levels may increase the risk of lung cancer development in patients with IPF.

Heat Exposure, Preterm Birth, and the Role of Greenness in Australia

Preterm birth (PTB) is associated with adverse health outcomes. The outcomes of heat exposure during pregnancy and the moderating association of greenness with PTB remain understudied. To investigate associations between heat exposure, greenness, and PTB, as well as interactions between these factors. Included in this cohort study were births occurring in Sydney, New South Wales, Australia, between 2000 and 2020, retrieved from New South Wales Midwives Data Collection. Participants with incomplete or missing data on their residential address or those who resided outside of New South Wales during their pregnancy were excluded. Data were analyzed from March to October 2023. Greenness measured using normalized difference vegetation index (NDVI) and tree cover derived from satellite images. Daily extreme heat and nighttime extreme heat were defined as above the 95th percentile of community- and trimester-specific daily mean temperatures and nighttime temperatures. Logistic regression models estimated the independent association of extreme heat with PTB, adjusting for individual- and area-level covariates, season of conception, and long-term trend. An interaction term between extreme heat exposure and greenness was included to explore potential modification. With a significant interaction observed, the number of preventable heat-associated PTBs that were associated with greenness was estimated. A total of 1 225 722 births (median [IQR] age, 39 [38-40] weeks; 631 005 male [51.5%]) were included in the analysis, including 63 144 PTBs (median [IQR] age, 35 [34-36] weeks; 34 822 male [55.1%]). Compared with those without heat exposure, exposure to daily extreme heat and nighttime extreme heat in the third trimester was associated with increased risks of PTB, with an adjusted odds ratio (OR) of 1.61 (95% CI, 1.55-1.67) and 1.51 (95% CI, 1.46-1.56]), respectively (PTB rates: exposed, 4615 of 61 338 [7.5%] vs unexposed, 56 440 of 1 162 295 [4.9%] for daily extreme heat and 4332 of 61 337 [7.1%] vs 56 723 of 1 162 296 [4.9%] for nighttime extreme heat). Disparities in associations between extreme heat exposure and PTB were observed, with lower odds of PTB among pregnant individuals residing in greener areas. The associations between extreme heat exposure and PTB could be mitigated significantly by higher greenness. Improving NDVI and tree cover could reduce daily extreme heat-associated PTB by 13.7% (95% CI, 2.3%-15.1%) and 20.9% (95% CI, 5.8%-31.5%), respectively. For nighttime extreme heat-associated PTB, reductions were 13.0% (0.2%-15.4%) and 17.2% (4.1%-27.0%), respectively. Results of this large birth cohort study suggest that extreme heat exposure was adversely associated with PTB, with greenness playing a moderating role. Increasing greenness levels in residential communities could prevent heat-associated PTBs. These findings emphasize the importance of integrating heat mitigation strategies and improving green space in urban planning and public health interventions.

Substance Use, Sleep Duration, and Health Among Adults in Ohio.

Substance use affects approximately 46.3 million people aged 12 years or older (16.5% of the US population) and is associated with poor sleep health overall. We conducted a cross-sectional secondary analysis of data from the 2020 Behavioral Risk Factor Surveillance System survey in Ohio. The sample comprised 14,676 adults. We examined associations between the use of 2 types of substances (marijuana and nonprescribed prescription pain medication) and short sleep duration (<6 hours per night) and overall health (mental, physical, and general). We used linear and logistic regression modeling while adjusting for individual-level (age, sex, race and ethnicity, education, income, and body mass index) and area-level (socioeconomic deprivation) covariates. Of survey respondents who answered questions, 9.2% (1,140 of 12,362) reported using marijuana, and 1.4% (111 of 8,203) used nonprescribed prescription pain medication. Respondents who used marijuana used it an average 17.3 days per month. In adjusted logistic regression models, the odds of reporting short sleep duration were 2.4 times greater among respondents who used nonprescribed prescription pain medication (vs those who did not). The odds of reporting short sleep duration, poor mental health, poor physical health, and poor general health were 1.5, 1.3, 2.1, and 1.9 times greater, respectively, among respondents who reported marijuana use (vs those who did not). In the linear regression models (adjusted), more days of marijuana use were associated with longer sleep duration, worse mental health, and worse general health. Understanding the connection between substance use and health outcomes is needed to improve trajectories of substance use and recovery. Sleep duration is often underassessed among people who use substances. Expanding diagnostics and treatment options for those who use substances may result in lower levels of substance use and improved overall health.

From childhood blue space exposure to adult environmentalism: The role of nature connectedness and nature contact

Nature contact in childhood is associated with pro-environmental behaviours (PEB) later in life. While previous literature focused on nature contact in general, the current work specifically explored childhood blue space exposure (coasts, rivers, lakes etc.) and potential mechanisms underlying any relationship with PEBs in adulthood. Cross-sectional data from an Austrian sample representative on age, gender, and region (N = 2,370) were used to test a serial-parallel mediation model linking recalled childhood blue space exposure to self-reported adult PEBs via, first, nature connectedness and, second, recent visits to green and blue spaces. Results supported significant serial mediation, with recalled childhood blue space exposure linked to nature connectedness in adulthood, which was in turn associated with more frequent recent visits to green and blue spaces, which in turn predicted PEB. Significant direct and indirect effects were observed, while controlling for known individual- and area-level covariates. Findings highlight the potential importance of childhood blue space exposure as well as life-long nature contact for improving nature connectedness and PEB and add to calls for protecting and maintaining natural water bodies and to improve their safety, as spending time around them in childhood may play a role in fostering PEB and ultimately improving planetary health.

Maternal greenness exposure and preterm birth in Brazil: A nationwide birth cohort study

In the dynamic landscape of maternal and child health, understanding the intricate interplay between environmental factors and pregnancy outcomes is of paramount importance. This study investigates the relationship between maternal greenness exposure and preterm births in Brazil using data spanning from 2010 to 2019. Satellite-derived indices, including the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were employed to assess greenness exposure during whole pregnancy in maternal residential area. Employing Cox proportional hazard models, we calculated the hazard ratios (HRs) with 95% confidence intervals (CIs) for changes in NDVI, while adjusting for individual and area-level covariates. In total, 24,010,250 live births were included. Prevalence of preterm birth was 11.5%, with a modest but statistically significant decreasing trend (p = 0.013) observed across the nation over the study period. The findings reveal a significant association between greenness exposure and a reduced risk of preterm birth. Specifically, for every 0.1 increase in NDVI, there was a 2.0% decrease in the risk of preterm birth (95%CI: 1.9%–2.2%). Stratified analyses based on maternal education and ethnicity indicated potential effect modifications, with stronger protective effects observed among younger mothers and those with less years of education. Sensitivity analyses using EVI yielded consistent results. In conclusion, this study suggests that higher maternal greenness exposure is linked to a decreased risk of preterm birth in Brazil. These findings imply that enhancing residential greenspaces could be a valuable public health strategy to promote maternal and child health in Brazil.

Spatial modelling of infectious diseases with covariate measurement error

Abstract In spatial infectious disease models, it is typical to assume that only the distance between susceptible and infectious individuals is important for modelling, but not the actual spatial locations of the individuals. Recently introduced geographically-dependent individual level models (GD-ILMs) can be used to also consider the effect of spatial locations of individuals and the distance between susceptible and infectious individuals for determining the risk of infection. In these models, it is assumed that the covariates used to predict the occurrence of disease are measured accurately. However, there are many applications in which covariates are prone to measurement error. For instance, to study risk factors for influenza, people with low socio-economic status (SES) are known to be more at risk compared to the rest of the population. However, SES is prone to measurement error. In this paper, we propose a GD-ILM which accounts for measurement error in both individual-level and area-level covariates. A Monte Carlo expectation conditional maximisation algorithm is used for inference. We use models fitted to data to predict areas with high average infectivity rates. We evaluate the performance of the proposed approach through simulation studies and by a real-data application on influenza data in Manitoba, Canada.

Long-term exposure to air pollution and incidence of mental disorders. A large longitudinal cohort study of adults within an urban area

BackgroundRecent epidemiological evidence suggests associations between air pollution exposure and major depressive disorders, but the literature is inconsistent for other mental illnesses. We investigated the associations of several air pollutants and road traffic noise with the incidence of different categories of mental disorders in a large population-based cohort. MethodsWe enrolled 1,739,277 individuals 30 + years from the 2011 census in Rome, Italy, and followed them up until 2019. In detail, we analyzed 1,733,331 participants (mean age 56.43 +/- 15.85 years; 54.96 % female) with complete information on covariates of interest. We excluded subjects with prevalent mental disorders at baseline to evaluate the incidence (first hospitalization or co-pay exemption) of schizophrenia spectrum disorders, bipolar, anxiety, personality, or substance use disorders. In addition, we studied subjects with first prescriptions of antipsychotics, antidepressants, and mood stabilizers. Annual average concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO₂), Black Carbon (BC), ultrafine particles (UFP), and road traffic noise were assigned to baseline residential addresses. We applied Cox regression models adjusted for individual and area-level covariates. ResultsEach interquartile range (1.13 µg/m3) increase in PM2.5 was associated with a hazard ratio (HR) of 1.070 (95 % confidence interval [CI]: 1.017, 1.127) for schizophrenia spectrum disorder, 1.135 (CI: 1.086, 1.186) for depression, 1.097 (CI: 1.030, 1.168) for anxiety disorders. Positive associations were also detected for BC and UFP, and with the three categories of drug prescriptions. Bipolar, personality, and substance use disorders did not show clear associations. The effects were highest in the age group 30–64 years, except for depression. ConclusionsLong-term exposure to ambient air pollution, especially fine and ultrafine particles, was associated with increased risks of schizophrenia spectrum disorder, depression, and anxiety disorders. The association of the pollutants with the prescriptions of specific drugs increases the credibility of the results.

A Primer on Clustering of Forest Management Units for Reliable Design-Based Direct Estimates and Model-Based Small Area Estimation

This study employs clustering analysis to group forest management units using auxiliary, satellite imagery-derived height metrics and past wall-to-wall tree census data from a natural, uneven-aged forest. Initially, we conducted an exhaustive exploration to determine the optimal number of clusters k, considering a wide range of clustering schemes, indices, and two specific k ranges. The optimal k is influenced by various factors, including the minimum k considered, the selected clustering algorithm, the clustering indices used, and the auxiliary variables. Specifically, the minimum k, the Euclidean distance metric, and the clustering index were instrumental in determining the optimal cluster numbers, with algorithms exerting minimal influence. Unlike traditional validation indices, we assessed the performance of these optimally defined clusters based on direct estimates and additional criteria. Subsequently, our research introduces a twofold methodology for Small Area Estimation (SAE). The first approach focuses on aggregating forest management units at the cluster level to increase the sample size, thereby yielding reliable design-based direct estimates for key forest attributes, including growing stock volume, basal area, tree density, and mean tree height. The second approach prepares area-level data for the future application of model-based estimators, contingent on establishing a strong correlation between target and auxiliary variables. Our methodology has the potential to enhance forest inventory practices across a wide range of forests where area-level auxiliary covariates are available.

Exploring the longitudinal associations between census division income inequality and BMI trajectories among Canadian adolescent: Is gender an effect modifier?

BackgroundIncome inequality is a structural determinant of health linked to increased risk of overweight and obesity, although its links to the health of adolescent populations are not well understood. This study investigated the longitudinal associations between census-division-level (CD) income inequality and BMI trajectories among Canadian adolescents, and determine if these associations vary by gender. MethodsStudy data are from the Cannabis use, Obesity, Mental health, Physical Activity, Alcohol use, Smoking, and Sedentary behaviour (COMPASS) cohort of adolescents attending secondary schools in Canada. Our sample included 14,675 adolescents who were followed up across three waves of the COMPASS study (2016–2017, 2017–2018, and 2018–2019) and linked to 30 CDs. Measures of income inequality and other area-level covariates were derived and linked to COMPASS participants using data from the 2016 Canadian Census. We utilized multilevel mixed-effects linear regression modelling to quantify the associations between income inequality and BMI and test for effect modification by gender. Sensitivity analyses were run excluding those with BMI scores in the range considered overweight or obesity at baseline. ResultsHigher CD income inequality was significantly associated with higher z-transformed BMI scores (β = 0.11, 95% CI = 0.034 to 0.19). The interaction term between income inequality and time was not statistically significant, indicating that this association remained constant over time. Once stratified by gender, the association between inequality and BMI became stronger for males (β = 0.14, 95% CI = 0.060 to 0.022) and attenuated for females (β = 0.063, 95% CI = −0.047 to 0.17). ConclusionAttending schools in CDs with higher income inequality was associated with higher BMI scores among male but not female adolescents. Further work is needed to investigate this discrepancy and identify the structural mechanisms that mediate the relationship between inequality and adolescent health.

Hypertension and Stroke as Mediators of Air Pollution Exposure and Incident Dementia

Fine particulate matter air pollution (PM2.5) has been consistently associated with cardiovascular disease, which, in turn, is associated with an increased risk of dementia. As such, vascular dysfunction might be a mechanism by which PM2.5 mediates dementia risk, yet few prior epidemiological studies have examined this potential mechanism. To investigate whether hypertension and stroke serve as mediators and modifiers of the association of PM2.5 with incident dementia. As part of the Environmental Predictors of Cognitive Health and Aging (EPOCH) Project, this cohort study used biennial survey data collected between 1998 and 2016 from respondents of the Health and Retirement Study (HRS), a nationally representative, population-based, cohort in the US. Eligible participants were those over 50 years of age who were free of dementia at baseline and had complete exposure, mediator, outcome, and demographic data from the HRS. Data analysis was conducted from August to November 2022. Exposure to PM2.5, calculated for the 10 years preceding each person's baseline examination according to residential histories and spatiotemporal models. Incident dementia was identified using a validated algorithm based on cognitive testing and informant reports. The 4-way decomposition causal mediation analysis method was used to quantify the degree to which hypertension and stroke mediated or modified the association of PM2.5 with incident dementia after adjustment for individual-level and area-level covariates. Among 27 857 participants (mean [SD] age at baseline, 61 [10] years; 15 747 female participants [56.5%]; 19 249 non-Hispanic White participants [69.1%]), 4105 (14.7%) developed dementia during the follow-up period (mean [SD], 10.2 [5.6] years). Among participants with dementia, 2204 (53.7%) had a history of hypertension at baseline and 386 (9.4%) received a diagnosis of hypertension during the follow up. A total of 378 participants (9.2%) had a history of stroke at baseline and 673 (16.4%) developed stroke over the follow-up period. The IQR of baseline PM2.5 concentrations was 10.9 to 14.9 μg/m3. In fully adjusted models, higher levels of PM2.5 (per IQR) were not associated with increased risk of incident dementia (HR, 1.04; 95% CI, 0.98 to 1.11). Although there were positive associations of prevalent stroke (HR, 1.67; 95% CI, 1.48 to 1.88) and hypertension (HR, 1.15; 95% CI, 1.08 to 1.23) with incident dementia compared with those free of stroke and hypertension during follow-up, there was no statistically significant association of PM2.5 with stroke (odds ratio per IQR increment in PM2.5, 1.08; 95%CI, 0.91 to 1.29) and no evidence of an association of PM2.5 with hypertension (odds ratio per IQR increment in PM2.5, 0.99; 95%CI, 0.92 to 1.07). Concordantly, there was no evidence that hypertension or stroke acted as mediators or modifiers of the association of PM2.5 with incident dementia. Although the nonmediated interaction between PM2.5 and hypertension accounted for 39.2% of the total excess association (95% CI, -138.5% to 216.9%), the findings were not statistically significant. These findings suggest that although hypertension may enhance the susceptibility of individuals to air pollution, hypertension and stroke do not significantly mediate or modify the association of PM2.5 with dementia, indicating the need to investigate other pathways and potential mediators of risk.

Associations between long-term aircraft noise exposure, cardiovascular disease, and mortality in US cohorts of female nurses.

Between 1994 and 2014, we followed 57,306 NHS and 60,058 NHSII participants surrounding 90 airports. Aircraft noise was modeled above 44 A-weighted decibels (dB(A)) and linked to geocoded addresses. Based on exposure distributions, we dichotomized exposures at 50 dB(A) and tested sensitivity of this cut-point by analyzing aircraft noise as categories (<45, 45-49, 50-54, ≥55) and continuously. We fit cohort-specific Cox proportional hazards models to estimate relationships between time-varying day-night average sound level (DNL) and CVD incidence and CVD and all-cause mortality, adjusting for fixed and time-varying individual- and area-level covariates. Results were pooled using random effects meta-analysis. Over 20 years of follow-up, there were 4529 CVD cases and 14,930 deaths. Approximately 7% (n = 317) of CVD cases were exposed to DNL ≥50 dB(A). In pooled analyses comparing ≥50 with <50 dB(A), the adjusted hazard ratio for CVD incidence was 1.00 (95% confidence interval: 0.89, 1.12). The corresponding adjusted hazard ratio for all-cause mortality was 1.02 (95% confidence interval: 0.96, 1.09). Patterns were similar for CVD mortality in NHS yet underpowered. Among participants in the NHS and NHSII prospective cohorts who generally experience low exposure to aircraft noise, we did not find adverse associations of aircraft noise with CVD incidence, CVD mortality, or all-cause mortality.

Accounting for Medicaid expansion and regional policy and programs to advance equity in cancer prevention in the United States.

Many studies compare state-level outcomes to estimate changes attributable to Medicaid expansion. However, it is imperative to conduct more granular, demographic-level analyses to inform current efforts on cancer prevention among low-income adults. Therefore, the authors compared the volume of patients with cancer and disease stage at diagnosis in Ohio, which expanded its Medicaid coverage in 2014, with those in Georgia, a nonexpansion state, by cancer site and health insurance status. The authors used state cancer registries from 2010 to 2017 to identify adults younger than 64 years who had incident female breast cancer, cervical cancer, or colorectal cancer. Multivariable Poisson regression was conducted by cancer type, health insurance, and state to examine the risk of late-stage disease, adjusting for individual-level and area-level covariates. A difference-in-differences framework was then used to estimate the differences in risks of late-stage diagnosis in Ohio versus Georgia. In Ohio, the largest increase in all three cancer types was observed in the Medicaid group after Medicaid expansion. In addition, significantly reduced risks of late-stage disease were observed among patients with breast cancer on Medicaid in Ohio by approximately 7% and among patients with colorectal cancer on Medicaid in Ohio and Georgia after expansion by approximately 6%. Notably, the authors observed significantly reduced risks of late-stage diagnosis among all patients with colorectal cancer in Georgia after expansion. More early stage cancers in the Medicaid-insured and/or uninsured groups after expansion suggest that the reduced cancer burden in these vulnerable population subgroups may be attributed to Medicaid expansion. Heterogeneous risks of late-stage disease by cancer type highlight the need for comprehensive evaluation frameworks, including local cancer prevention efforts and federal health policy reforms. This study looked at how Medicaid expansion affected cancer diagnosis and treatment in two states, Ohio and Georgia. The researchers found that, after Ohio expanded their Medicaid program, there were more patients with cancer among low-income adults on Medicaid. The study also found that, among people on Medicaid, there were lower rates of advanced cancer at the time of diagnosis for breast cancer and colon cancer in Ohio and for colon cancer in Georgia. These findings suggest that Medicaid expansion may be effective in reducing the cancer burden among low-income adults.

Long-term exposure to ultrafine particles and natural and cause-specific mortality

BackgroundHealth implications of long-term exposure to ubiquitously present ultrafine particles (UFP) are uncertain. The aim of this study was to investigate the associations between long-term UFP exposure and natural and cause-specific mortality (including cardiovascular disease (CVD), respiratory disease, and lung cancer) in the Netherlands. MethodsA Dutch national cohort of 10.8 million adults aged ≥ 30 years was followed from 2013 until 2019. Annual average UFP concentrations were estimated at the home address at baseline, using land-use regression models based on a nationwide mobile monitoring campaign performed at the midpoint of the follow-up period. Cox proportional hazard models were applied, adjusting for individual and area-level socio-economic status covariates. Two-pollutant models with the major regulated pollutants nitrogen dioxide (NO2) and fine particles (PM2.5 and PM10), and the health relevant combustion aerosol pollutant (elemental carbon (EC)) were assessed based on dispersion modelling. ResultsA total of 945,615 natural deaths occurred during 71,008,209 person-years of follow-up. The correlation of UFP concentration with other pollutants ranged from moderate (0.59 (PM2.5)) to high (0.81 (NO2)). We found a significant association between annual average UFP exposure and natural mortality [HR 1.012 (95 % CI 1.010–1.015), per interquartile range (IQR) (2723 particles/cm3) increment]. Associations were stronger for respiratory disease mortality [HR 1.022 (1.013–1.032)] and lung cancer mortality [HR 1.038 (1.028–1.048)] and weaker for CVD mortality [HR 1.005 (1.000–1.011)]. The associations of UFP with natural and lung cancer mortality attenuated but remained significant in all two-pollutant models, whereas the associations with CVD and respiratory mortality attenuated to the null. ConclusionLong-term UFP exposure was associated with natural and lung cancer mortality among adults independently from other regulated air pollutants.

Long-Term Exposure to Ambient Air Pollution and Mortality among Four Million COVID-19 Cases in Italy: The EpiCovAir Study.

The role of chronic exposure to ambient air pollutants in increasing COVID-19 fatality is still unclear. The study aimed to investigate the association between long-term exposure to air pollutants and mortality among 4 million COVID-19 cases in Italy. We obtained individual records of all COVID-19 cases identified in Italy from February 2020 to June 2021. We assigned 2016-2019 mean concentrations of particulate matter (PM) with aerodynamic diameter (), PM with aerodynamic diameter (), and nitrogen dioxide () to each municipality () as estimates of chronic exposures. We applied a principal component analysis (PCA) and a generalized propensity score (GPS) approach to an extensive list of area-level covariates to account for major determinants of the spatial distribution of COVID-19 case-fatality rates. Then, we applied generalized negative binomial models matched on GPS, age, sex, province, and month. As additional analyses, we fit separate models by pandemic periods, age, and sex; we quantified the numbers of COVID-19 deaths attributable to exceedances in annual air pollutant concentrations above predefined thresholds; and we explored associations between air pollution and alternative outcomes of COVID-19 severity, namely hospitalizations or accesses to intensive care units. We analyzed 3,995,202 COVID-19 cases, which generated 124,346 deaths. Overall, case-fatality rates increased by 0.7% [95% confidence interval (CI): 0.5%, 0.9%], 0.3% (95% CI: 0.2%, 0.5%), and 0.6% (95% CI: 0.5%, 0.8%) per increment in , , and , respectively. Associations were higher among elderly subjects and during the first (February 2020-June 2020) and the third (December 2020-June 2021) pandemic waves. We estimated COVID-19 deaths were attributable to pollutant levels above the World Health Organization 2021 air quality guidelines. We found suggestive evidence of an association between long-term exposure to ambient air pollutants with mortality among 4 million COVID-19 cases in Italy. https://doi.org/10.1289/EHP11882.

Long-term exposure to traffic-related air pollution and non-accidental mortality: A systematic review and meta-analysis

BackgroundThe health effects of traffic-related air pollution (TRAP) continue to be of important public health interest across the globe. Following its 2010 review, the Health Effects Institute appointed a new expert Panel to systematically evaluate the epidemiological evidence regarding the associations between long-term exposure to TRAP and selected health outcomes. This paper describes the main findings of the systematic review on non-accidental mortality. MethodsThe Panel used a systematic approach to conduct the review. An extensive search was conducted of literature published between 1980 and 2019. A new exposure framework was developed to determine whether a study was sufficiently specific to TRAP, which included studies beyond the near-roadway environment. We performed random-effects meta-analysis when at least three estimates were available of an association between a specific exposure and outcome. We evaluated confidence in the evidence using a modified Office of Health Assessment and Translation (OHAT) approach, supplemented with a broader narrative synthesis. ResultsThirty-six cohort studies were included. Virtually all studies adjusted for a large number of individual and area-level covariates—including smoking, body mass index, and individual and area-level socioeconomic status—and were judged at a low or moderate risk for bias. Most studies were conducted in North America and Europe, and a few were based in Asia and Australia. The meta-analytic summary estimates for nitrogen dioxide, elemental carbon and fine particulate matter—pollutants with more than 10 studies—were 1.04 (95% CI 1.01, 1.06), 1.02 (1.00, 1.04) and 1.03 (1.01, 1.05) per 10, 1 and 5 µg/m3, respectively. Effect estimates are interpreted as the relative risk of mortality when the exposure differs with the selected increment. The confidence in the evidence for these pollutants was judged as high, because of upgrades for monotonic exposure–response and consistency across populations. The consistent findings across geographical regions, exposure assessment methods and confounder adjustment resulted in a high confidence rating using a narrative approach as well. ConclusionsThe overall confidence in the evidence for a positive association between long-term exposure to TRAP and non-accidental mortality was high.

Long-Term Exposure to Air Pollution and COVID-19 Vaccine Antibody Response in a General Population Cohort (COVICAT Study, Catalonia).

Ambient air pollution has been associated with COVID-19 disease severity and antibody response induced by infection. We examined the association between long-term exposure to air pollution and vaccine-induced antibody response. This study was nested in an ongoing population-based cohort, COVICAT, the GCAT-Genomes for Life cohort, in Catalonia, Spain, with multiple follow-ups. We drew blood samples in 2021 from 1,090 participants of 2,404 who provided samples in 2020, and we included 927 participants in this analysis. We measured immunoglobulin M (IgM), IgG, and IgA antibodies against five viral-target antigens, including receptor-binding domain (RBD), spike-protein (S), and segment spike-protein (S2) triggered by vaccines available in Spain. We estimated prepandemic (2018-2019) exposure to fine particulate matter [PM in aerodynamic diameter ()], nitrogen dioxide (), black carbon (BC), and ozone () using Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) models. We adjusted estimates for individual- and area-level covariates, time since vaccination, and vaccine doses and type and stratified by infection status. We used generalized additive models to explore the relationship between air pollution and antibodies according to days since vaccination. Among vaccinated persons not infected by SARS-CoV-2 (), higher prepandemic air pollution levels were associated with a lower vaccine antibody response for IgM (1 month post vaccination) and IgG. Percentage change in geometric mean IgG levels per interquartile range of () were (95% CI: , 0.4) for RBD, (, ) for S, and (, ) for S2. We observed a similar pattern for and BC and an inverse pattern for . Differences in IgG levels by air pollution levels persisted with time since vaccination. We did not observe an association of air pollution with vaccine antibody response among participants with prior infection (). Exposure to air pollution was associated with lower COVID-19 vaccine antibody response. The implications of this association on the risk of breakthrough infections require further investigation. https://doi.org/10.1289/EHP11989.